TSA-MS characterization and kinetic study of the pyrolysis process of various types of biomass based on the Gaussian multi-peak fitting and peak-to-peak approaches

Janković, Bojan; Manić, Nebojša; Stojiljković, Dragoslava; Jovanović, Vladimir

doi:10.1016/j.fuel.2018.07.051

Cited by 34 publications

(11 citation statements)

References 43 publications

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“…So, this behavior is not unusual considering that both, cellulose and hemicelluloses degradation includes a series of decomposition reaction pathways which cannot be described by the simple integer reaction-order kinetics, because the complicated reactions related to entire apricot kernel shell pyrolysis. On the other hand, in all considered cases, it can be observed that the kinetic parameters (Ea and A) calculated by the Janković et al [30], are in good agreement with those derived from the model (Table 3). On the other hand, the pseudo-component fraction X related to each component varies slightly with the change of the heating rate (Table 3), and theoretically calculated pseudo-component fraction values are arranged in the following order: PSC-4 < PSC-3 < PSC-2 < PSC-1.…”

Section: Results Of Kinetic Modellingsupporting

confidence: 74%

“…Using the algorithm described in the methodology section, the simulation was performed between 3 and 5 pseudo-components, but the best fit quality results show the data related to four pseudo-components model. Also, the proposed kinetic model includes composition analysis with already presented methodology [30].…”

Section: Results Of Kinetic Modellingmentioning

confidence: 99%

“…The brief summary of the complete methodology used in this paper is shown in Figure 1, and is presented in detail in the literature [26]. Application of the selected methodology together with peak to peak analysis approach could also provide calculation of kinetic parameters of each biomass PSC as well as pseudo-component fraction (Xi) at considered heating rate, which could be used for composition analysis of the selected material [30].…”

Section: Multicomponent Kinetic Modellingmentioning

confidence: 99%

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Multicomponent Modelling Kinetics and Simultaneous Thermal Analysis of Apricot Kernel Shell Pyrolysis

Manić¹,

Janković²,

Dodevski³

et al. 2020

J. sustain. dev. energy water environ. syst.

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Apricot kernel shells are naturally available source of biomass with potential for conversion to clean energy through a thermo-chemical process such as pyrolysis. To facilitate further process development, an advanced mathematical model which represents the process kinetics is developed and validated on the thermal decomposition studies using simultaneous thermal analysis, over a temperature range of 30-900 °C, at four heating rates of 5, 10, 15 and 20 °C min −1 , under argon atmosphere. Model-free analysis and numerically developed methods were utilized for determination of effective activation energies, pre-exponential factors and the fractional contribution. A novel approach is introduced in order to determine actual pseudo-components of studied biomass that are included in its composition. The comparative study of the obtained kinetic results was also presented. The results obtained strongly indicated that the pseudo-component reaction modelling method could be employed to predict the experimental devolatilization rate and biomass composition with a high likelihood of success.

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Section: Results Of Kinetic Modellingsupporting

confidence: 74%

Section: Results Of Kinetic Modellingmentioning

confidence: 99%

Section: Multicomponent Kinetic Modellingmentioning

confidence: 99%

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Multicomponent Modelling Kinetics and Simultaneous Thermal Analysis of Apricot Kernel Shell Pyrolysis

Manić¹,

Janković²,

Dodevski³

et al. 2020

J. sustain. dev. energy water environ. syst.

View full text Add to dashboard Cite

show abstract

“…For this, the overlapped differential kinetic curves derived from TGA data were deconvoluted into multiple pseudo-components associated with contributions of extractives, hemicellulose, cellulose, and lignin, by using the Gaussian multi-peak fitting function. This mathematical function has been successfully employed in dealing with lignocellulosic biomass pyrolysis [3,19], which often exhibits a pyrolytic behavior with multistep kinetics. For this study, the pseudo-component peaks were extracted using the Microsoft Excel® software and Gaussian function.…”

Section: Kinetic Studymentioning

confidence: 99%

“…In this respect, mathematical tools such as deconvolution fitting functions can extract the several parallel reactions of biomass pyrolysis and provide accurate values of the kinetic triplet [15]. Among the different deconvolution fitting functions found in literature, the Gaussian multi-peak fitting function has proven to be an effective method to extract the single reactions associated with lignocellulosic pseudo-components [3,19]. The description of each reaction in biomass pyrolysis, reached from deconvolution, can be used in the Vyazovkin isoconversional method to provide suitable kinetic data for biomass pyrolysis.…”

Section: Introductionmentioning

confidence: 99%

Pyrolysis of cocoa shell and its bioenergy potential: evaluating the kinetic triplet, thermodynamic parameters, and evolved gas analysis using TGA-FTIR

Mumbach

Alves

Silva

et al. 2020

Biomass Conv. Bioref.

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This study presents the first attempt to focus on the cocoa shell pyrolysis in terms of kinetic triplet, thermodynamic parameters, and evolved volatile analysis using the TGA-FTIR technique. For reliable interpretation of the multistep pyrolysis of cocoa shell, the multiple kinetic triplets were adequately estimated by a combined kinetic procedure using five independent parallel reactions with the Vyazovkin isoconversional method, the compensation effect, and the master plot method. According to the results, the multiple kinetic triplets were able to describe the pyrolysis behavior of the cocoa shell with an accuracy of R 2 > 0.9446 and the pyrolysis mechanisms exhibited different reaction models (n-order and contracting cylinder). Evolved volatile analysis suggested the presence of high-energy compounds (aromatic) and useful chemicals (aldehyde, ketone, esters, ether, and alcohols). The pre-exponential factors for the five pseudo-components of cocoa shell pyrolysis ranged from 2.56 × 10 11 to 8.66 × 10 16 min −1 (derived from the compensation effect method), while the values of E a ranged from 99 to 271 kJ mol −1 . From a comparative analysis, it was found that the results from the compensation effect method ensured the overall kinetic expression to be consistent with the experimental cocoa shell pyrolysis behavior. In contrast, the overall kinetic expression using pre-exponential factors derived from Kissinger's method failed to match the experimental curves. The pyrolytic conversion of cocoa shell into bioenergy appeared as potentially viable (E a -ΔH ≤ 5.5 kJ mol −1 ). The promising findings on the cocoa shell pyrolysis can expand the use of this residue in bioenergy applications, consisting of a great attempt toward its valorization.

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The Pyrolysis of Waste Biomass Investigated by Simultaneous TGA-DTA-MS Measurements and Kinetic Modeling with Deconvolution Functions

Manić

Janković

Dodevski

et al. 2019

Computational and Experimental Approaches in Materials Science and Engineering

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TSA-MS characterization and kinetic study of the pyrolysis process of various types of biomass based on the Gaussian multi-peak fitting and peak-to-peak approaches

Cited by 34 publications

References 43 publications

Multicomponent Modelling Kinetics and Simultaneous Thermal Analysis of Apricot Kernel Shell Pyrolysis

Multicomponent Modelling Kinetics and Simultaneous Thermal Analysis of Apricot Kernel Shell Pyrolysis

Pyrolysis of cocoa shell and its bioenergy potential: evaluating the kinetic triplet, thermodynamic parameters, and evolved gas analysis using TGA-FTIR

The Pyrolysis of Waste Biomass Investigated by Simultaneous TGA-DTA-MS Measurements and Kinetic Modeling with Deconvolution Functions

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